2025
Markov Parameters Generation for Data-based Modeling of Tensegrity Robots Considering Finite Word-Length Effects
IROS 2025
This paper studies the impact of finite word-length effects on the Markov parameters of tensegrity robots during digital simulations. First, the round-off noise models are introduced, where round-off noise is applied to the system’s inputs, outputs, and states. The deterministic and stochastic defin